Quorum sensing and the anaerobic regulator (ANR) control polyhydroxyalkanoate (PHA) production in<i>Pseudomonas chlororaphis</i>PA23
Bibliographic record
Abstract
Pseudomonas chlororaphis PA23 is a biocontrol agent that, in addition to producing antifungal compounds, synthesizes polyhydroxyalkanoate (PHA) polymers as a carbon and energy sink. Quorum sensing (QS) and the anaerobic regulator (ANR) are required for PA23-mediated fungal suppression; however, the role of these regulators in PHA production is unknown. Strains lacking either QS or ANR accumulated less PHA polymers when propagated on Ramsay's minimal medium (RMM) with glucose or octanoate as the carbon source. In the acyl-homoserine lactone (AHL)-deficient background, all six of the genes in the pha locus (phaC1, phaC2, phaZ, phaD, phaF, phaI) showed reduced expression in RMM glucose, and all except phaC2 were repressed in RMM octanoate. Although changes in gene activity were observed in the anr mutant, they were less pronounced. Analysis of the promoter regions for QS- and ANR-binding consensus sequences revealed putative phzboxes upstream of phaZ and phaI, but no anr boxes were identified. Our findings indicate that altered pha gene expression likely contributes to the lower PHA accumulation in the QS- and ANR-deficient strains, which may be in part indirectly mediated. This study is the first to show that mcl-PHA production is under QS and ANR control.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".